A variety of methods are known for detecting behavior-based associations (associations based on user behaviors) between items stored or represented in a database. For example, the purchase histories or item viewing histories of users can be analyzed to detect behavior-based associations between particular items represented in an electronic catalog (e.g., items A and B are related because a relatively large number of those who purchased A also purchased B). See, e.g., U.S. Pat. No. 6,912,505. As another example, the web browsing histories of users can be analyzed to identify behavior-based associations between particular web sites and/or web pages. See, e.g., U.S. Pat. No. 6,691,163 and U.S. Pat. Pub. 2002/0198882.
The detected behavior-based associations are typically used to assist users in locating items of interest. For example, in the context of an electronic catalog, when a user accesses a network resource, such as a web page, that is associated with an item, the resource may be supplemented with a list of related items. This list may, for example, be preceded with a descriptive message such as “people who bought this item also bought the following,” or “people who viewed this item also viewed the following.” The detected associations may also be used to generate personalized recommendations that are based on the target user's purchase history, item viewing history, and/or other item selections.
In some instances, however, behavior-based associations may generate low quality associations or no associations at all for certain items. The quantity of behavioral data collected for a particular item, for instance, may be insufficient to create behavior-based associations for that item. This may be the case when new items are added to an electronic catalog or when new web pages or documents are added to a data repository. In addition, the quantity of behavioral data can also be insufficient to create behavior-based associations for items that are rarely purchased.
Behavior-based associations can also generate low-quality associations for popular items. Popular items tend to be associated behaviorally with many other items simply because many people buy the popular items along with other unrelated items. As a result, for example, a best selling novel might become behaviorally-associated with an unrelated item such as a pen knife.